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Kernel Function-Based Primal-Dual Interior-Point Methods for Symmetric Cones Optimization
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作者 ZHAO Dequan ZHANG Mingwang 《Wuhan University Journal of Natural Sciences》 CAS 2014年第6期461-468,共8页
In this paper, we present a large-update primal-dual interior-point method for symmetric cone optimization(SCO) based on a new kernel function, which determines both search directions and the proximity measure betwe... In this paper, we present a large-update primal-dual interior-point method for symmetric cone optimization(SCO) based on a new kernel function, which determines both search directions and the proximity measure between the iterate and the center path. The kernel function is neither a self-regular function nor the usual logarithmic kernel function. Besides, by using Euclidean Jordan algebraic techniques, we achieve the favorable iteration complexity O( √r(1/2)(log r)^2 log(r/ ε)), which is as good as the convex quadratic semi-definite optimization analogue. 展开更多
关键词 symmetric cones optimization Kernel function Interior-point method polynomial complexity
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Sum-of-Squares Design Method for Four-Parameter Lag-Lead Compensator
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作者 李志恒 尹胜超 +1 位作者 张毅 李力 《Tsinghua Science and Technology》 SCIE EI CAS 2009年第6期732-734,共3页
The four-parameter lag-lead compensator design has received much attention in the last two decades. However, most approaches have been either trial-and-error or only for special cases. This paper presents a non-trial-... The four-parameter lag-lead compensator design has received much attention in the last two decades. However, most approaches have been either trial-and-error or only for special cases. This paper presents a non-trial-and-error design method for four-parameter lag-lead compensators. Here, the compensator design problem is formulated into a polynomial function optimization problem and solved by using the recently developed sum-of-squares (SOS) techniques. This result not only provides a useful design method but also shows the power of the SOS techniques. 展开更多
关键词 lag-lead compensator polynomial function optimization sum of squares (SOS) semi-definite programming (SDP)
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